Bob Pease, analog engineer at National Semiconductor and writer at EDN Magazine, used to say, “when something seems funny, measure the amount of funny.” That’s easier done in the engineering domain than the people domain, of course.

These two simple guidelines will help:

1. Measure the things you really care about. Too many people collect numbers that are based on guesses or on indefinable units. If you’re measuring productivity, figure out a way to measure delivered, working features, not “story points” or other estimates. Jack gave an example where, to increase the number of circuit boards being produced, the technicians were not bothering to repair the boards that didn’t work. They were tossing them aside, creating a pile of waste inventory. In Jack’s example, the productivity measurement only measured part of what was desired.

2. Use measurements to illuminate, not as a goal. As Michael Bolton says, good metrics allow you to ask better questions. They don’t answer them. The productivity numbers mentioned above didn’t say how productive the workers were being, because it didn’t show the wasted inventory.

Measuring things is a great way to sharpen the observations. It’s still an observation, though. Sometimes you can observe things that you can’t measure. In that case of a “strong feeling of ‘things are better,'” you may not be able to measure how much better. But you can still ask the data question, “What have you seen or heard that makes you think things are better?”

Comments (1) to “Process Metrics”

“In it, Jack cautions against relying on ‘a strong feeling that “things are better.”‘” (Wow, I’ve forced three quote marks in a row.)

I’m intrigued by the next bit: “He recommends using measurements to bring it back to the realm of engineering.”

That’s interesting, in light of the fact that the decision about whether “things are better” is an emotional decision, perhaps informed by rational notions, but not itself strictly rational. People don’t make decisions based on the numbers; they make decisions based on how they feel about the numbers. For many people, relying on “the realm of engineering” allows them to feel better about an evaluation of what’s “better”. But as you point out, George, “that’s easier done in the engineering domain than the people domain, of course.” As a consequence of feeling better about quantitative evaluations, managers and owners often create environments in which engineering values take precedence over people values. Yet what happens when we have an excellent engineering solution (the asssembly line comes to mind) in which the workers become mechanized, bored, and miserable?